AI Engineer

accessiBe; New York (NY); On-site; USD 119,000 - 161,000; Full time

Job summary

accessiBe is hiring an AI GTM Engineer to design, build, and own the GTM technology layer powering marketing and revenue operations. This engineer will architect systems that connect CRM, marketing automation, data warehouses, and AI agents for scalable go-to-market workflows.

The role demands production-grade integrations, robust data models, and cross-functional collaboration with Marketing and RevOps. Hybrid NYC work (3 days on-site) is expected, with a focus on durable, scalable architecture

Qualifications

• Weeks of hands-on, applied GTM or growth engineering experience in a technical role.
• Minimum 1 year of hands-on, applied AI/LLM development with shipped projects.
• Deep production API integrations experience, including OAuth, webhooks, rate limits, and error handling.
• Admin/API proficiency with HubSpot or Salesforce and data-model thinking.
• Based in or willing to work hybrid in New York City (3 days on-site in Flatiron).
• Strong ability to translate technical decisions into language for marketing and sales teams.

Responsibilities

• Design and own the integrated GTM architecture connecting CRM, marketing automation, data warehouse, and AI layers.
• Build multi-agent AI workflows to automate go-to-market motions at scale with maintainability.
• Create robust integrations across the GTM stack spanning HubSpot, Salesforce, Clay, ZoomInfo and data systems.
• Design data models and pipelines for accurate pipeline, attribution, and campaign insight.
• Document work and establish engineering standards for API management and monitoring.

Skills

API integrations

OAuth flows

Webhook reliability

Rate limiting

Error handling

HubSpot API

Salesforce API

Data models

Tools

HubSpot

Salesforce

Clay

ZoomInfo

Ad platforms

Job description

New York City (Hybrid, 3 days/week) | compensation: $140,000 base salary

About accessiBe

accessiBe is the market leader in web accessibility that makes websites accessible to people with disabilities. We are more than a workplace—we're a mission. Each day you're surrounded by people who share the same goal and values, working relentlessly to break down accessibility barriers and ensure the web works for everyone, regardless of ability. We hire people determined to succeed who thrive in rapid change. We care deeply about excellence, sincerity, and the meaningful work of making digital inclusion a reality for the millions of people navigating the web with disabilities.

About the Role

We are hiring an AI GTM Engineer to design, build, and own the GTM technology layer that powers accessiBe's marketing and revenue operations. This is an engineering role embedded in go-to-market—not a marketer who uses AI tools, but a builder who understands GTM deeply enough to architect the systems that make it run.

The person we're looking for has a track record of building integrated GTM systems that organizations actually depend on—not a collection of point-solution automations, but coherent architectures connecting CRM, marketing automation, data pipelines, and AI agent workflows into something that compounds over time. You think about schemas, API contracts, authentication patterns, failure handling, and scalability before you write the first line. You've seen what happens when someone builds fast and loose, and you've cleaned it up. AI is giving the GTM function enormous leverage—but only if the underlying systems are built with rigor. That's what this role is about.

What You'll Do

• Design and own the integrated architecture connecting our CRM, marketing automation platform, data warehouse, and AI agent layer—with intentionality about how data flows, where it lives, and how systems talk to each other
• Build multi-agent AI workflows that automate and orchestrate go-to-market motions at scale, with clear ownership, monitoring, and maintainability baked in from the start
• Build robust integrations across the GTM stack—HubSpot, Salesforce, Clay, ZoomInfo, ad platforms, and the data systems that tie them together
• Design data models and reporting pipelines that give Marketing and RevOps accurate, consistent insight into pipeline, attribution, and campaign performance
• Build AI agent systems—not one-off prompts, but coordinated agent architectures—that meaningfully accelerate marketing operations, demand generation, and sales coordination
• Evaluate and integrate new AI tooling against a clear standard: does it fit the system architecture, can it be maintained, and does it create durable value rather than fragility?
• Establish engineering standards for how the marketing team builds and integrates tools: API management, credential handling, webhook reliability, and integration monitoring
• Partner directly with cross-functional stakeholders to scope initiatives efficiently and deliver durable systems
• Document your work so that teams can maintain and extend it independently

What We Need

• 2-5 years in a technical GTM, marketing engineering, growth engineering, or applied AI/LLM role— with demonstrable experience building systems, not just configuring tools
• A minimum of one year of hands‑on, applied AI/LLM development experience, with the ability to speak in depth to the technical approach behind a shipped project
• Deep experience with production API integrations—you understand OAuth flows, webhook reliability, rate limiting, error handling, and what it means to build an integration that holds up in production
• HubSpot or Salesforce at an admin/API depth—not just user-level familiarity, but the ability to design data models and build on top of the platform
• Based in or willing to work hybrid in New York City (3 days/week on‑site in Flatiron)
• Strong communication skills—you can translate technical architecture decisions into plain language for marketing and sales stakeholders

Strong Plus

• Background in software engineering, solutions architecture, or technical consulting—you've worked in an engineering‑first environment and brought that discipline into GTM
• Experience building multi-agent AI systems using frameworks like Claude, OpenAI, LangChain, or similar in a production GTM context
• Data engineering experience: dbt, Snowflake, BigQuery, or equivalent—you understand the data layer beneath the tools
• Experience with Clay, Apollo, ZoomInfo, or outbound orchestration tooling—at an integration and architecture level, not just as an end user
• Startup or scale‑up experience where you've had to build infrastructure and execute simultaneously
• B2B SaaS company experience
• Exposure to the accessibility, compliance, or enterprise risk management industries

Office address: 1140 Broadway, New York, NY 10001